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<p>This paper investigates safety-constrained control problem in multi-UAV formation systems considering both unknown time-varying disturbances and actuator faults. To enhance the disturbance rejection capability of the system, an immersion-and-invariance disturbance observer is developed to accurately estimate disturbances in real-time. Then, an adaptive sliding mode fault-tolerant formation controller is proposed to ensure consensus in multi-UAV systems, which incorporates a neural network to compensate for system uncertainties. Building on the fault-tolerant formation controller, high-order control barrier functions are incorporated into a locally formulated quadratic programming for each UAV to ensure inter-UAV and obstacle avoidance safety, which minimally adjusts the fault-tolerant formation control input only when safety constraints become active. Numerical simulations and real-time experiments demonstrate the effectiveness and safety performance of the proposed control strategy.</p>

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Immersion and invariance disturbance observer-based fault-tolerant formation control of multi-UAVs under safety constraints

  • 期刊论文

  • 发表日期：

    2026年6月29日

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  • Ruian Wang,
  • Wei Hao,
  • Tong Mei,
  • Wenlai Ma

摘要

This paper investigates safety-constrained control problem in multi-UAV formation systems considering both unknown time-varying disturbances and actuator faults. To enhance the disturbance rejection capability of the system, an immersion-and-invariance disturbance observer is developed to accurately estimate disturbances in real-time. Then, an adaptive sliding mode fault-tolerant formation controller is proposed to ensure consensus in multi-UAV systems, which incorporates a neural network to compensate for system uncertainties. Building on the fault-tolerant formation controller, high-order control barrier functions are incorporated into a locally formulated quadratic programming for each UAV to ensure inter-UAV and obstacle avoidance safety, which minimally adjusts the fault-tolerant formation control input only when safety constraints become active. Numerical simulations and real-time experiments demonstrate the effectiveness and safety performance of the proposed control strategy.